基于非支配排序遗传算法的振动主动控制优化方法

非支配排序遗传算法是一种基于Pareto前沿的低计算需求、有精英策略、约束处理简单的多目标优化算法。该算法能够搜索到Pareto解集，由专家根据具体要求进行客观的筛选，根据各个目标函数不同的加权进行合理选择最优解，满足了不同研究目的对同一系统的不同要求，这是单目标优化算法不可比拟的。以结构振动系统的结构振动能量和系统控制能量作为多目标优化函数，建立了振动主动控制系统的控制增益以及传感器和作动器位置、数量和长度的多目标优化配置数学模型，首次利用非支配排序遗传算法作为优化策略，并以悬臂梁作为算例，进行了仿真实验，验证了该方法的有效性和可行性。

Active Vibration Control Optimization Based on NSGA-II

Fast and elitist multi-objective genetic algorithm（NSGA-Ⅱ） is based on Pareto-optimal front with low computation requirement, elitist approach, and simple constraint-handling strategy. NSGA-Ⅱ can search the representative and satisfactory Pareto-optimal solutions for expert to objectively select the optimal solution according to weight values of objective functions and different purposes, which is the incomparable advantage over single-objective optimization algorithm. Taking structure vibration energy and system control energy as multi-objective optimization functions of a structure vibration system, an multi-objective optimal disposition model is established including placement, quantity and length of sensors and actuators, and control gain of active vibration control system. A cantilever simulation with NSGA-Ⅱ as optimization strategy verifies the effectiveness and feasibility of the presented method.